Print Email Facebook Twitter Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns Title Ontology-Based Reflective Communication for Shared Human-AI Recognition of Emergent Collaboration Patterns Author van Zoelen, E.M. van den Bosch, K. Abbink, D. Neerincx, M.A. Contributor Aydoğan, R. (editor) Criado, N. (editor) Lang, J. (editor) Sanchez-Anguix, V. (editor) Serramia, M. (editor) Publication year 2023 Abstract When humans and AI-agents collaborate, they need to continuously learn about each other and the task. We propose a Team Design Pattern that utilizes adaptivity in the behavior of human and agent team partners, causing new Collaboration Patterns to emerge. Human-AI Co-Learning takes place when partners can formalize recognized patterns of collaboration in a commonly shared language, and can communicate with each other about these patterns. For this, we developed an ontology of Collaboration Patterns. An accompanying Graphical User Interface (GUI) enables partners to formalize and refine Collaboration Patterns, which can then be communicated to the partner. The ontology was evaluated empirically with human participants who viewed video recordings of joint human-agent activities. Participants were requested to identify Collaboration Patterns in the footage, and to formalize patterns by using the ontology’s GUI. Results show that the ontology supports humans to recognize and define Collaboration Patterns successfully. To improve the ontology, it is suggested to include pre- and post-conditions of tasks, as well as parallel actions of team members. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG. Subject OntologyCollaboration PatternsCo-learningBehavioral researchGraphical user interfacesVideo recordingAdaptivityConditionDesign PatternsHuman-agent teamsLearn+Ontology'sOntology-basedTeam designsOntology To reference this document use: http://resolver.tudelft.nl/uuid:12b7626d-5c2c-4dd3-b2aa-dd50d643fd2c DOI https://doi.org/10.1007/978-3-031-21203-1_40 TNO identifier 980194 ISBN 9783031212024 Source Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 24th International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020, 16 November 2022 through 18 November 2022, 13753 (13753), 621-629 Series Lecture Notes in Computer Science Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.